Design and Analysis of Single-Case Research

By Ronald D. Franklin; David B. Allison et al. | Go to book overview

be used as covariates to statistically partial out the effects of cyclicity should be obtained. If such control measures are not available, time of observation can be used as a covariate with one of various regression- based trend analysis approaches. It should be noted that cyclical processes may not have a linear function and, therefore, models should be based on a nonlinear analyses (i.e., curvilinear regression, differencing). From these considerations, it is believed that researchers and consumers alike can judge for themselves the plausibility of threat posed by cyclicity.


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Design and Analysis of Single-Case Research
Table of contents

Table of contents

  • Title Page iii
  • Contents v
  • Preface vii
  • References x
  • Contributors xiii
  • List of Equations xix
  • 1: Introduction 1
  • Introduction 1
  • References 10
  • 2: Historical and Philosophical Foundations of Single-Case Research 13
  • References 39
  • 3: Measurement of Dependent Variables 41
  • References 84
  • 4: Treatment Integrity in Single-Subject Research 93
  • 5: Graphical Display and Visual Analysis1 119
  • Introduction 119
  • References 154
  • 6: Statistical Alternatives for Single-Case Designs 159
  • References 208
  • 7: Serial Dependency in Single-Case Time Series 215
  • Introduction 215
  • References 242
  • 8: Meta-Analysis of Single-Case Research 245
  • Introduction 245
  • SUMMARY 273
  • References 273
  • 9: The Potentially Confounding Effects of Cyclicity: Identification, Prevention, and Control 279
  • References 328
  • Appendix 334
  • 10: Power, Sample Size Estimation, and Early Stopping Rules 335
  • Introduction 335
  • SUMMARY 367
  • References 368
  • Author Index 373
  • Subject Index 383


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